Circulating Expression Level of LncRNA Malat1 in Diabetic Kidney Disease Patients and Its Clinical Significance

Zhou, Lian-Ji; Yang, Dawei; Ou, Li-na; Guo, Xiaokui; Wu, Biaoliang

doi:10.1155/2020/4729019

Cited by 28 publications

(25 citation statements)

References 31 publications

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“…Metastasis-associated lung adenocarcinoma transcript 1, also known as Neat2 (Malat1) is one of the most analyzed lncRNAs in DKD samples. The qualitative analysis showed that lncRNAs were expressed in serum, urine, peripheral blood mononuclear cells, and kidney tissue [ 29 , 30 , 36 , 37 , 39 ]. There were increased expressions of lncRNA MALAT1 in DKD, translocation of β -catenin to the nucleus, enhanced expressions of MALAT1 connexin serine/arginine splicing factor 1 (SRSF1), and expressions of p-cadherin and tight junction protein ZO-1.…”

Section: Discussionmentioning

confidence: 99%

The Impact of lncRNA on Diabetic Kidney Disease: Systematic Review and In Silico Analyses

Zhao

Yan

et al. 2022

Computational Intelligence and Neuroscience

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Background. Long noncoding RNA (lncRNA) is involved in the occurrence and development of diabetic kidney disease (DKD). It is necessary to identify the expression of lncRNA from DKD patients through systematic reviews, and then carry out silico analyses to recognize the dysregulated lncRNA and their associated pathways. Methods. The study searched Pubmed, Embase, Cochrane Library, WanFang, VIP, CNKI, and CBM to find lncRNA studies on DKD published before March 1, 2021. Systematic review of the literature on this topic was conducted to determine the expression of lncRNA in DKD and non-DKD controls. For the dysregulated lncRNA in DKD patients, silico analysis was performed, and lncRNA2Target v2.0 and starBase were used to search for potential target genes of lncRNA. The Encyclopedia of Genomics (KEGG) pathway enrichment analysis was performed to better identify dysregulated lncRNAs in DKD and determine the associated signal pathways. Results. According to the inclusion and exclusion criteria, 28 publications meeting the eligibility criteria were included in the systematic evaluation. A total of 3,394 patients were enrolled in this study, including 1,238 patients in DKD group, and 1,223 diabetic patients, and 933 healthy adults in control group. Compared with the control, there were eight lncRNA disorders in DKD patients (MALAT1, GAS5, MIAT, CASC2, NEAT1, NR_033515, ARAP1-AS2, and ARAP1-AS1). In addition, five lncRNAs (MALAT1, GAS5, MIAT, CASC2, and NEAT1) participated in disease-related signal pathways, indicating their role in DKD. Discussion. This study showed that there were eight lncRNAs in DKD that were persistently dysregulated, especially five lncRNAs which were closely related to the disease. Although systematic review included 28 studies that analyzed the expression of lncRNA in DKD-related tissues, the potential of these dysregulated lncRNAs as biomarkers or therapeutic targets for DKD remains to be further explored. Trial registration. PROSPERO (CRD42021248634).

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Section: Discussionmentioning

confidence: 99%

The Impact of lncRNA on Diabetic Kidney Disease: Systematic Review and In Silico Analyses

Zhao

Yan

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

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“…The association of MALAT1 with inflammatory factors has been shown in various studies [ 37 , 38 , 39 ]. Different studies have shown that MALAT1 expression is increased in diabetes-related complications, including diabetic cardiomyopathy, diabetic kidney disease, diabetic retinopathy, and gestational diabetes [ 40 , 41 , 42 , 43 , 44 ]. Hu et al.…”

Section: Discussionmentioning

confidence: 99%

The axis of long non-coding RNA MALAT1/miR-1-3p/CXCR4 is dysregulated in patients with diabetic neuropathy

Ashjari

Karamali

Rajabinejad

et al. 2022

Heliyon

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“…For example, circulating long noncoding RNA DKFZP434I0714 was reported to predict adverse cardiovascular outcomes in patients with end-stage renal disease [19]. Circulating lncRNA Malat1 was found to be highly expressed in diabetic nephropathy patients, which is expected to be a new target for the diagnosis of diabetic nephropathy [20]. More and more lncRNAs in CKD remain to be characterized, and systematic pro ling of lncRNAassociated ceRNA network analysis is needed to identify hub genes and reveal the regulatory mechanisms involved in the pathogenesis of CKD.…”

Section: Discussionmentioning

confidence: 99%

Construction of a lncRNA‐associated ceRNA regulatory network to explore the pathogenesis of chronic kidney disease

Huang

Sun

2022

Preprint

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Background: Chronic kidney disease (CKD) is characterized by high morbidity and mortality rate worldwide, and is considered a major public health problem. Studies have shown that long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) may be involved in the biological processes of CKD, but the exact mechanisms are still largely unknown. In this study, further analysis of these ceRNA networks will reveal the important role of ceRNAs in the pathogenesis of CKD.Methods: Differentially expressed (DE) lncRNAs in CKD patients and healthy volunteers were identified through high-throughput sequencing. Functional enrichment analysis was performed to examine the key biological functions and pathways involved in CKD. The lncRNA‐associated ceRNA regulatory network was constructed, and a protein-protein interaction (PPI) network analysis was conducted to identify the hub genes involved in the pathogenesis of CKD. Results: In this study, 378 DE lncRNAs were detected, of which 207 were intergenic lncRNAs, 88 were intronic lncRNAs and 83 were exonic lncRNAs. The intergenic lncRNAs have 96 up-regulated lncRNAs and 111 down-regulated lncRNAs. As for intronic lncRNAs, 39 lncRNAs were up-regulated and 49 were down-regulated. Similarly, we also found that 27 exonic lncRNAs were up-regulated and 56 were down-regulated. Functional enrichment analysis was performed based on the prediction of lncRNA‐miRNA-mRNA interactions. GO analysis showed that predicted target gene was highly correlated with the immune response. KEGG analysis revealed that predicted target genes were significantly enriched in regulated pathways such as MAPK signaling pathway. We successfully constructed lncRNA‐associated ceRNA regulatory network involved in the pathogenesis of CKD, and based on this network, a PPI network was established to identify 10 hub genes which participate in the pathogenesis of CKD.Conclusions: Our findings provide a new perspective understanding of the lncRNA‐associated ceRNA network involved in CKD, which may help to elucidate the potential pathogenesis of CKD.

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Circulating Expression Level of LncRNA Malat1 in Diabetic Kidney Disease Patients and Its Clinical Significance

Cited by 28 publications

References 31 publications

The Impact of lncRNA on Diabetic Kidney Disease: Systematic Review and In Silico Analyses

The Impact of lncRNA on Diabetic Kidney Disease: Systematic Review and In Silico Analyses

The axis of long non-coding RNA MALAT1/miR-1-3p/CXCR4 is dysregulated in patients with diabetic neuropathy

Construction of a lncRNA‐associated ceRNA regulatory network to explore the pathogenesis of chronic kidney disease

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